Combining Multi-Engine Translations with Moses
نویسندگان
چکیده
We present a simple method for generating translations with the Moses toolkit (Koehn et al., 2007) from existing hypotheses produced by other translation engines. As the structures underlying these translation engines are not known, an evaluationbased strategy is applied to select systems for combination. The experiments show promising improvements in terms of BLEU.
منابع مشابه
Multi-Engine Machine Translation with an Open-Source Decoder for Statistical Machine Translation
We describe an architecture that allows to combine statistical machine translation (SMT) with rule-based machine translation (RBMT) in a multi-engine setup. We use a variant of standard SMT technology to align translations from one or more RBMT systems with the source text. We incorporate phrases extracted from these alignments into the phrase table of the SMT system and use the open-source dec...
متن کاملMulti-Engine Machine Translation with an Open-Source SMT Decoder
We describe an architecture that allows to combine statistical machine translation (SMT) with rule-based machine translation (RBMT) in a multi-engine setup. We use a variant of standard SMT technology to align translations from one or more RBMT systems with the source text. We incorporate phrases extracted from these alignments into the phrase table of the SMT system and use the open-source dec...
متن کاملPredictive Models of Performance in Multi-Engine Machine Translation
The paper describes a novel approach to Multi-Engine Machine Translation. We build statistical models of performance of translations and use them to guide us in combining and selecting from outputs from multiple MT engines. We empirically demonstrate that the MEMT system based on the models outperforms any of its component engine.
متن کاملA Case Study of German into English by Machine Translation: to Evaluate MOSES using MOSES for Mere Mortals
This paper evaluates the usefulness of Moses, an open source statistical machine translation (SMT) engine, for professional translators and post editors. It takes a look behind the scenes at the workings of Moses and reports on experiments to investigate how translators can contribute to advances in the use of SMT as a tool. In particular the difference in quality of output was compared as the ...
متن کاملMulti-Engine Machine Translation by Recursive Sentence Decomposition
In this paper, we present a novel approach to combine the outputs of multiple MT engines into a consensus translation. In contrast to previous Multi-Engine Machine Translation (MEMT) techniques, we do not rely on word alignments of output hypotheses, but prepare the input sentence for multi-engine processing. We do this by using a recursive decomposition algorithm that produces simple chunks as...
متن کامل